Join us for the 2019 Gibbons Lecture Series. This is the last lecture in the series and involves a panel discussion with quantum computing experts Professor Howard J Carmichael and Professor Cristian S Calude.

Join us for the 2019 Gibbons Lecture Series. In third of four lectures, Professor Bremner will discuss how quantum advantage emerges from the subtle characteristics of problems where quantum interference can best be utilised.

The New Zealand Space Agency and SpaceBase have gathered a panel of experts and space students for a public discussion and Q & A. Come and join us to discuss space, and hear about the growing opportunities in this fast-moving, high-tech sector. This is a free TechWeek event, which has been supported by the Faculty of Science's Our World and Universe research theme.

Join us for the 2019 Gibbons Lecture Series. In this talk, Professor Steven Galbraith will briefly survey modern cryptography and indicate which current systems are potentially vulnerable to quantum computers.

Join us for the 2019 Gibbons Lecture Series. In this first of four lectures, Dr Michael Dinneen will give an explanation (for novices) of what quantum computing is, and compare it to traditional digital/classical computing.

In this talk, Dr Christian Gaser, Hood Fellow from the University of Jena, will demonstrate the underlying concept of this so-called BrainAGE approach, including methodological details. He will also demonstrate various applications, ranging from creating a frame of reference for neurodevelopmental trajectories early in life, to the identification of protective and risk factors later in life.

In the last of the 2019 Ihaka lecture series, Professor Robert Tibshirani will review the lasso method for high dimensional supervised learning and discuss some new developments in the area. he will also describe some applications of these methods to his own collaborative work.

Professor Douglas Elliffe from the School of Psychology will present his recent research that suggests reinforcement signals future successful behaviour, as well as some thoughts about the place of teaching and leadership in an academic's career.

In the third of the 2019 Ihaka lecture series, Dr Kristian Lum will demonstrate how – if considerations of fairness and bias are not explicitly accounted for – predictive models could perpetuate and, under some circumstances, amplify undesirable historical biases encoded in the data.

For thousands of years, calculation (numerical and symbolic) was the price we had to pay to do or use mathematics. But now we have machines that can handle far more variables than a human ever could, they never make mistakes, and they do it in a fraction of a second. Join Professor Keith Devlin from Stanford as he explains what math professionals do and how we teach the next generation to live and work in this world.

The emergence of “fake news” along with sophisticated techniques using machine learning to create realistic looking media such as Deep Fakes, has led to a resurgent interest in digital media forensics. In this talk, Professor Nasir Memon will broadly discuss how media has traditionally been generated and detected.

In the second lecture of the 2019 Ihaka lecture series, Professor Thomas Lumley (Department of Statistics) will talk about about how deep convolutional nets are structured and give some intuition for how they can be effective.

Launching our 2019 Ihaka Lecture Series, Professor Bernhard Pfahringer will introduce a number of open-source Machine Learning software suites, reflect on their design decisions and issues, and try to position them in the current international Machine Learning landscape.

Fancy up to US$40,000 towards masters or doctoral study in the USA? Find out how to make that dream come true at the Fulbright New Zealand information session on Wednesday 13 March. Awards open to NZ citizens and permanent residents. Please register to attend.

Professor Mykola Pechenizkiy discusses how modern predictive analytics and machine learning techniques contribute to the massive automation of the data-driven decision making and decision support. It becomes better understood and accepted, in particular due to the new General Data Protection Regulation (GDPR), that employed predictive models may need to be audited.

In this seminar Dr Matt Baker (School of Biotechnology and Biomolecular Sciences and EMBL Australia Node for Single Molecule Science, University of New South Wales, Australia) will discuss his work as a biophysicist who examines generating and sensing forces in biology.